
@article{pmid19505943,
    title = {{The Sequence Alignment/Map format and SAMtools.}},
    author = {Heng Li and Bob Handsaker and Alec Wysoker and Tim Fennell and Jue Ruan and Nils Homer and Gabor Marth and Goncalo Abecasis and Richard Durbin and  },
    journal = {{Bioinformatics}},
    volume = {25},
    number = {16},
    year = {2009},
    month = aug,
    pages = {2078-9},
    abstract = {SUMMARY: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. AVAILABILITY: http://samtools.sourceforge.net.},
    pii = {btp352},
    doi = {10.1093/bioinformatics/btp352},
    pubmed = {19505943},
    pmc = {PMC2723002},
    nlmuniqueid = {9808944}
}


@article{pmid21208982,
    title = {{Tabix: fast retrieval of sequence features from generic TAB-delimited files.}},
    author = {Heng Li},
    journal = {{Bioinformatics}},
    volume = {27},
    number = {5},
    year = {2011},
    month = mar,
    pages = {718-9},
    abstract = {Tabix is the first generic tool that indexes position sorted files in TAB-delimited formats such as GFF, BED, PSL, SAM and SQL export, and quickly retrieves features overlapping specified regions. Tabix features include few seek function calls per query, data compression with gzip compatibility and direct FTP/HTTP access. Tabix is implemented as a free command-line tool as well as a library in C, Java, Perl and Python. It is particularly useful for manually examining local genomic features on the command line and enables genome viewers to support huge data files and remote custom tracks over networks. AVAILABILITY AND IMPLEMENTATION: http://samtools.sourceforge.net.},
    pii = {btq671},
    doi = {10.1093/bioinformatics/btq671},
    pubmed = {21208982},
    pmc = {PMC3042176},
    nlmuniqueid = {9808944}
}


@article{pmid21984761,
    title = {{Knime4Bio: a set of custom nodes for the interpretation of Next Generation Sequencing data with KNIME.}},
    author = {Pierre Lindenbaum and Solena Le Scouarnec and Vincent Portero and Richard Redon},
    journal = {{Bioinformatics}},
    year = {2011},
    month = oct,
    pages = {},
    abstract = {SUMMARY:  Analysing large amounts of data generated by next-generation sequencing (NGS) technologies is difficult for researchers or clinicians without computational skills. They are often compelled to delegate this task to computer biologists working with command line utilities. The availability of easy-to-use tools will become essential with the generalisation of NGS in research and diagnosis. It will enable investigators to handle much more of the analysis. Here, we describe Knime4Bio, a set of custom nodes for the KNIME (The Konstanz Information Miner) interactive graphical workbench, for the interpretation of large biological datasets. We demonstrate that this tool can be utilised to quickly retrieve previously published scientific findings. AVAILABILITY:  http://code.google.com/p/knime4bio/. CONTACT:  richard.redon@univ-nantes.fr.},
    pii = {btr554},
    doi = {10.1093/bioinformatics/btr554},
    pubmed = {21984761},
    nlmuniqueid = {9808944}
}

